Sunday, March 26, 2017

Rethinking Big Storm Warnings and Guaranteed Handwringing

With winter winding down, communications-strategy-rethinking season
begins. As surely as the snowflakes melt in the spring, there is a storm
to have angst over. This time, of course, it’s the blizzard that
wasn’t… in the big cities.

New Jersey Governor Christie has the
answer: Blame the meteorologists! As if we could somehow suddenly
conjure up better science. You would think that someone who has lived in
New Jersey as long as the governor would understand the rain-snow line
dilemma. If an unforecastable difference in the storm track means
somewhere between debilitating and nuisance, you’d better err on the
side of shutting things down. Unless, of course, you don’t mind the New
Jersey Turnpike looking like the Long Island Expressway did in 2013.
Thousands of stranded people in stuck cars and trucks, and a cleanup
nightmare that took days to resolve.

On the other hand, the
National Weather Service has confidence in their science, but can’t
decide on the best approach to putting up warnings. Should they be
aggressive? Should they wait until the last minute? It’s a conundrum in
search of a plan.

It seems to me that the National Weather
Service is in a no-win box as long as they stick with the current
paradigm of putting up warnings if the forecast weather meets certain
thresholds. If X amount of snow is going to fall in Y amount of time
with Z wind and T temperature, we put up a Blizzard Warning. No amount
of social-science research is going to better inform the decision of
when or whether to put up the warning. It comes down to the confidence
of the forecaster that the weather will meet the threshold, with
consideration of the amount of time left until the event starts. Nobody
wants drivers or trains trapped in a blizzard. Obviously in the case of
Winter Storm Stella earlier this month, the NWS forecasters had
sufficient confidence and concern for the potential consequences to pull
the trigger on a Blizzard Warning for New York and Boston.

The
onus is on the forecasters. Be sure your confidence, concern, and
crystal ball are working perfectly, or you’ll hear from the governor.
But there’s another way. Since confidence underlies the process, why not
let confidence set the thresholds? Call it Plan CCC for Critical
Confidence Calculation.

National Weather Service websites, the
Capital Weather Gang, and others already publish boom or bust odds. The
Mount Holly, New Jersey local National Weather Service Forecast Office
has a page with the odds of every imaginable possible snow or ice
accumulation the storm might produce. The odds for wind and temperature
thresholds could easily be added, if they had a mind to. They could
easily overwhelm us with enough stats that we couldn’t possibly have any
confidence in the forecast. It’s approaching that now.

So why
not generate the odds that the weather will reach the Winter Storm
Warning threshold, or the Blizzard Warning threshold, or the threshold
for anything you want. Just tell the computer and voila, you’ve got a
map with contours that show where there’s a 10%, 20%, etc. chance of the
Blizzard Warning being required.

Get buy-in in advance from
everybody involved, including the loudmouth politicians, on what the
odds should be when the trigger is pulled, and the NWS is largely out of
the blame game. If the governor is happy to shut down the turnpike if
there is at least a one-in-five chance of thousands of his residents
getting stranded, set the threshold at 20%. It’s a simple risk-tolerance
exercise puts decision-makers’ skin in the game.

Even if the
NWS can’t get a consensus, at least the numbers would be public. Between
the social scientists and inclusive outreach, it would be doable.

In
practice, of course, it is not quite this simple. What happens if the
forecaster believes the models are underplaying or overplaying the risk?
How are close calls handled? If the threshold is X and the X line is
dancing around New York City, what’s the move? But at least this system
starts with a baseline risk that key players are involved in setting.
With the warning underpinned by a risk they agreed on, when the time
runs out, issue the warning.

The communications from the
politicians would change as well. Now we hear, “The National Weather
Service says we’re getting two feet of snow so we’re shutting down the
city.” The new paradigm would result in something like, “The storm
threat has reached the level where we can’t take a chance on people
being stranded and infrastructure being damaged, so were closing down.”

The bottom line: use the science to get the monkey off the forecasters’ backs.